# How Envoy uses Harness

**bi-weekly** Frequency of experiments run

As published on [harness.io](https://www.harness.io/case-studies/how-envoy-optimizes-value-with-feature-flags-experimentation), August 2026. Captured by usedby on 2026-10-09.

- Company: [Envoy](https://www.usedby.ai/companies/envoy.md)
- Tool: [Harness](https://www.usedby.ai/tools/harness.md)
- Teams: Product, Engineering, Design, Support

## What the story says

Envoy uses Split's feature flagging and experimentation platform (now part of Harness FME) to wrap new features in flags, run phased rollouts, and run regular experiments that measure business impact. Product managers launch rollouts themselves without needing developers to set them up manually.

Summary written by usedby from the source page, in English. The figures are those of Harness and Envoy, not ours.

> Envoy evolved from simply rolling out features to running continuous experiments, allowing them to track and optimize business impact in real-time.

> Split has enabled us to test, release, and experiment at a scale that directly impacts our revenue. We're now able to launch experiments every two weeks, testing new features and measuring results in real-time.
>
> Eric Crane, Product Manager

Source: [harness.io](https://www.harness.io/case-studies/how-envoy-optimizes-value-with-feature-flags-experimentation), captured 2026-10-09.

## What usedby checked

We compared the story with its live page on 2026-10-09.

- Checked: the figure bi-weekly is on the page; its label is our wording.
- Checked: the passage quoted above is copied word for word from the page, near the name of Envoy.
- Checked: the publication date is read from the page’s own metadata, never guessed.
- Checked: Envoy uses Harness. Confirmed line. Latest check across sources: 2026-10-09.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/envoy-harness · How we check: https://www.usedby.ai/methodology